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### Building

Start with building your *<%= engine_name %>* engine. Run the following command:

```
$ pio build --verbose
```

This command should take few minutes for the first time; all subsequent builds
should be less than a minute. You can also run it without `--verbose` if you don't want to see all the log messages.

Upon successful build, you should see a console message similar to the
following.

```
[INFO] [Console$] Your engine is ready for training.
```

### Training the Predictive Model

To train your engine, run the following command:

```
$ pio train
```

When your engine is trained successfully, you should see a console message
similar to the following.

```
[INFO] [CoreWorkflow$] Training completed successfully.
```

### Deploying the Engine

Now your engine is ready to deploy. Run:

```
$ pio deploy
```

When the engine is deployed successfully and running, you should see a console message similar to the following:

```
[INFO] [HttpListener] Bound to /0.0.0.0:8000
[INFO] [MasterActor] Bind successful. Ready to serve.
```

Do not kill the deployed engine process.

By default, the deployed engine binds to http://localhost:8000. You can visit
that page in your web browser to check its status.

![Engine Status](/images/engine-server.png)
